Abstract: The invention provides a corneal path one-way aqueous humor drainage device, in which a Tesla valve unit group drainage channel is formed for draining aqueous humor to the ocular surface, and the drainage channel is a one-way drainage. The aqueous humor diverter provided by the utility model introduces a Tesla valve as a structure to prevent the backflow of aqueous humor. When the liquid flows into the Tesla valve unit group from the liquid outlet, the Tesla valve unit group can block the liquid from entering the liquid. Oral flow. The aqueous humor drainage device can be used for glaucoma patients to reduce intraocular pressure and can also be used for severe dry eye; it is made of materials with good biocompatibility and has high clinical drainage efficiency; its structure.

Abstract: Systems and methods are disclosed for question generation to obtain more related medical information based on observed symptoms from a patient. In embodiments, possible diseases associated with the observed symptoms are generated by querying a knowledge graph. In embodiments, candidate symptoms associated with the possible diseases are also identified and are combined with the observed symptoms to obtain combined symptom sets. In embodiments, discriminative scores for the candidate symptom sets are determined and candidate symptoms with top discriminative scores are selected. In embodiments, these selected candidate symptoms may be checked for conflicts with observed symptoms and removed from further consideration if a conflict exists. In embodiments, one or more questions may be generated based on the remaining selected candidate systems to aid in collecting information about the patient. In embodiments, the process may be repeated with the updated observed symptoms.

Abstract: Presented are systems and methods that allow healthcare providers and governments to infer demand for healthcare resources to ensure effective and timely healthcare services to patients by reducing healthcare supply shortages, emergencies, and healthcare costs. In embodiments, this is accomplished by gathering data from a number of sources to generate labeled records from which entity features and relationships between entities are extracted, correlates, and/or combined with other external healthcare data. In embodiments, this information is used to train a model that predicts healthcare resource demands given a set of input conditions or factors.

Abstract: Various embodiments relate to a method and non-transitory computer readable medium for genome spelling correction, the method including the steps of performing pre-processing on a sentence, storing a first adjacent word to an unknown word and a second adjacent word to the unknown word, generating a plurality of candidate words for the unknown word, forming a plurality of trigrams with the first adjacent word to the unknown word and the second adjacent word to the unknown word and each of the plurality of candidate words, searching a trigram table for each of the plurality of trigrams and outputting the candidate word from the trigram with a highest trigram count in the trigram table.

Abstract: The disclosed embodiments provide a system for identifying root causes of performance issues. During operation, the system obtains a call graph containing a set of call paths for a set of services. Next, the system determines, based on a load test of the set of services, severity scores for the set of services, wherein the severity scores represent levels of abnormal behavior in the set of services. The system then groups the severity scores by the set of call paths and identifies, based on the grouped severity scores, one or more services as potential root causes of performance issues in the set of services. Finally, the system outputs the identified one or more services as the potential root causes of the performance issues.

Abstract: The present disclosure relates to a visual field testing method, system, and testing apparatus based on head-mounted testing equipment. The method includes: transmitting, by the testing apparatus in electronic equipment, a start notification for starting monitoring of a movement trajectory of a pupil of a current eye to be tested to an eye movement tracking system after receiving a start test instruction transmitted from a controller; receiving, by the testing apparatus, movement state information of the pupil that is transmitted from the eye movement tracking system; and determining, by the testing apparatus, the movement trajectory of the pupil according to the movement state information, wherein the controller is a component that is associated with the head-mounted testing equipment and communicatively connected to the testing apparatus of the electronic equipment.

Abstract: The disclosed embodiments provide a system for identifying root causes of performance issues. During operation, the system obtains a call graph containing a set of call paths for a set of services. Next, the system determines, based on a load test of the set of services, severity scores for the set of services, wherein the severity scores represent levels of abnormal behavior in the set of services. The system then groups the severity scores by the set of call paths and identifies, based on the grouped severity scores, one or more services as potential root causes of performance issues in the set of services. Finally, the system outputs the identified one or more services as the potential root causes of the performance issues.

Abstract: Retina digital imaging system, instrument and method A retina digital imaging system includes: an illumination module (1), a main optical assembly (3), and an image sensor module (2); the illumination module (1) includes light-emitting diodes capable of emitting light with different wavelengths, and each light-emitting diode emits light to enter the retina through the main optical assembly (3) to form an illumination optical path; the light reflected by the retina passes through the main optical assembly (3) and forms an image on the image sensor module (2) to form an imaging optical path. The various spectral bands formed by light-emitting diodes may form a wider spectrum, so different layers of the retina may be imaged to provide valuable medical and diagnostic data.

Abstract: The present disclosure relates to a visual field testing method, system, and testing apparatus based on head-mounted testing equipment (02). The method includes: transmitting, by the testing apparatus in electronic equipment (01), a start notification for starting monitoring of a movement trajectory of a pupil of a current eye to be tested to an eye movement tracking system (03) after receiving a start test instruction transmitted from a controller; receiving, by the testing apparatus, movement state information of the pupil (202) that is transmitted from the eye movement tracking system (03); and determining, by the testing apparatus, the movement trajectory (203) of the pupil according to the movement state information, wherein the controller is a component that is associated with the head-mounted testing equipment (02) and communicatively connected to the testing apparatus of the electronic equipment (01). The method can reduce the testing complexity and may also improve the testing accuracy and comfort.

Abstract: Disclosed are systems, methods, and non-transitory computer-readable media for automated profile image generation based on scheduled video conferences. A profile image generation system generates, based on image data captured during a first video conference, a first facial feature data set for a first identified face identified from the image data. The first facial feature data set includes numeric values representing the first identified face. The profile image generation system calculates, based on the first facial feature data set and historic facial feature data sets generated from image data captured during previous video conferences, a first value indicating a likelihood that the first identified face is a first meeting participant that participated in the first video conference. The profile image generation system determines that the first value meets or exceeds a threshold value, and in response, determines that the first identified face is the first meeting participant.

Abstract: Systems and methods are disclosed to identify entities that have a similar meaning, and may, in embodiments, be grouped into entity groups for knowledge base construction. In embodiments, the entity relations of similarity or non-similarity for an entity pair are predicted as a binary relationship. In embodiments, the prediction may be based upon similarity score between the entities and the entity features, which features are constructed using an entity feature or representation model. In embodiments, the prediction may be an iterative process involving minimum human checking and existing knowledge update. In embodiments, one or more entity groups are formed using graph search from the predicted entity pairs. In embodiments, a group centroid entity may be selected to represent each group based on one or more factors, such as its generality or popularity.

Abstract: Disclosed are systems, methods, and non-transitory computer-readable media for automated profile image generation based on scheduled video conferences. A profile image generation system generates, based on image data captured during a first video conference, a first facial feature data set for a first identified face identified from the image data. The first facial feature data set includes numeric values representing the first identified face. The profile image generation system calculates, based on the first facial feature data set and historic facial feature data sets generated from image data captured during previous video conferences, a first value indicating a likelihood that the first identified face is a first meeting participant that participated in the first video conference. The profile image generation system determines that the first value meets or exceeds a threshold value, and in response, determines that the first identified face is the first meeting participant.

Abstract: Methods, systems, and computer programs are presented for calculating a hyperparameter value set for training a machine-learning program (MLP). One method includes an operation for identifying a model for the MLP that comprises hyperparameter value sets to be tested based on a dataset that has performance data for features of the MLP. The method further includes operations for breaking the dataset into fragments for evaluating the model with a graphics processing unit (GPU) and for loading the cores of the GPU with the model and a respective hyperparameter value set. Each fragment of the dataset is streamed to a GPU memory, and the cores of the GPU evaluate, in parallel, the fragment based on the model and the respective hyperparameter value set. Further, the method includes operations for determining, storing, and presenting the best hyperparameter value set for the MLP.

Abstract: The disclosed embodiments provide a system for managing the execution of a statistical model. During operation, the system tracks a distribution of one or more metrics related to a performance of a first version of a statistical model. When a deviation in the distribution is detected, the system outputs an alert of an anomaly in the performance of the statistical model. The system also triggers a rollback to a second version of the statistical model.

Abstract: Presented are systems and methods that allow healthcare providers and governments to infer demand for healthcare resources to ensure effective and timely healthcare services to patients by reducing healthcare supply shortages, emergencies, and healthcare costs. In embodiments, this is accomplished by gathering data from a number of sources to generate labeled records from which entity features and relationships between entities are extracted, correlates, and/or combined with other external healthcare data. In embodiments, this information is used to train a model that predicts healthcare resource demands given a set of input conditions or factors.

Abstract: Systems and methods are disclosed provide improved automated extraction of medical-related information. In embodiments, finer-grained medical-related data, such as medical entities, including symptoms, diseases, dimensions, and temporal information, can be extracted. In embodiments, by extracted finer level medical-related information from an input statement and generating visual displays of that information, a medical professional can readily see relevant medical information that provides medical entities and associated dimension information, as well as evolving history.

Abstract: Systems and methods are disclosed to identify entities that have a similar meaning, and may, in embodiments, be grouped into entity groups for knowledge base construction. In embodiments, the entity relations of similarity or non-similarity for an entity pair are predicted as a binary relationship. In embodiments, the prediction may be based upon similarity score between the entities and the entity features, which features are constructed using an entity feature or representation model. In embodiments, the prediction may be an iterative process involving minimum human checking and existing knowledge update. In embodiments, one or more entity groups are formed using graph search from the predicted entity pairs. In embodiments, a group centroid entity may be selected to represent each group based on one or more factors, such as its generality or popularity.

Abstract: Systems and methods are disclosed for question generation to obtain more related medical information based on observed symptoms from a patient. In embodiments, possible diseases associated with the observed symptoms are generated by querying a knowledge graph. In embodiments, candidate symptoms associated with the possible diseases are also identified and are combined with the observed symptoms to obtain combined symptom sets. In embodiments, discriminative scores for the candidate symptom sets are determined and candidate symptoms with top discriminative scores are selected. In embodiments, these selected candidate symptoms may be checked for conflicts with observed symptoms and removed from further consideration if a conflict exists. In embodiments, one or more questions may be generated based on the remaining selected candidate systems to aid in collecting information about the patient. In embodiments, the process may be repeated with the updated observed symptoms.

Abstract: A method and an apparatus for establishing and using a user recommendation model in a social network. The method includes obtaining training data from the social network, performing heterogeneous data transfer learning on the training data to learn a semanteme of the training data, establishing an association between a user and the image data by using the text data as a medium, establishing a semantic association relationship between the image data and the user according to the semanteme of the training data and the association between the user and the image data, and establishing a user recommendation model according to the semantic association relationship, where the user recommendation model includes the semantic association relationship between the image data and the user.

Abstract: Disclosed are a hand-held vision detecting device and a method for using the hand-held vision detecting device to realize various eyesight measurements without wearing glasses and the steps therefor, wherein the hand-held vision detecting device at least comprises: an imaging lens group consisting of at least one imaging lens and an eye chart. The cornea of the subject can be located at the focal point at one side f the imaging lens group. The center of the eye chart is provided at the other side of the imaging lens group and can move forwards and backwards along the optical path. People can detect vision anytime and anywhere through this device and detection method via simple and easy operations, and the detection results are accurate.